WSS.RdThis function is a wrapper for siteSelection and reportingRateModel that
allows users the run a well sampled sites analysis as in Roy et al (2012).
WSS(taxa, site, time_period, minL = 2, minTP = 3, species_to_include = unique(taxa), overdispersion = FALSE, family = "Binomial", verbose = FALSE, print_progress = FALSE)
| taxa | A character vector of taxon names, as long as the number of observations. |
|---|---|
| site | A character vector of site names, as long as the number of observations. |
| time_period | A numeric vector of user defined time periods, or a date vector, as long as the number of observations. |
| minL | numeric, The minimum number of taxa recorded at a site at a given time period (list-length) for the visit to be considered well sampled. |
| minTP | numeric, The minimum number of time periods, or if time_period is a date the minimum number of years, a site must be sampled in for it be be considered well sampled. |
| species_to_include | A character vector giving the name of species to model. By default all species will be modelled |
| overdispersion | This option allows modelling overdispersion ( |
| family | The type of model to be use. Can be |
| verbose | This option, if |
| print_progress | Logical, if |
A dataframe of results are returned to R. Each row gives the results for a
single species, with the species name given in the first column, species_name.
For each of the following columns the prefix (before ".") gives the covariate and the
sufix (after the ".") gives the parameter of that covariate.
number_observations gives the number of visits where the species of interest
was observed. If any of the models encountered an error this will be given in the
column error_message.
The data.frame has a number of attributes:
intercept_year - The year used for the intercept (i.e. the
year whose value is set to 0). Setting the intercept to the median year helps
to increase model stability
min_year and max_year - The earliest and latest year
in the dataset (after years have been centered on intercept_year
nVisits - The total number of visits that were in the dataset
model_formula - The model used, this will vary depending on the
combination of arguements used
minL - The setting of minL used in site selection
minTP - The setting of minTP used in site selection
Roy, H.E., Adriaens, T., Isaac, N.J.B. et al. (2012) Invasive alien predator causes rapid declines of native European ladybirds. Diversity & Distributions, 18, 717-725.
# Create data n <- 1500 #size of dataset nyr <- 8 # number of years in data nSamples <- 20 # set number of dates # Create somes dates first <- as.POSIXct(strptime("2003/01/01", "%Y/%m/%d")) last <- as.POSIXct(strptime(paste(2003+(nyr-1),"/12/31", sep=''), "%Y/%m/%d")) dt <- last-first rDates <- first + (runif(nSamples)*dt) # taxa are set as random letters taxa <- sample(letters, size = n, TRUE) # three sites are visited randomly site <- sample(c('one', 'two', 'three'), size = n, TRUE) # the date of visit is selected at random from those created earlier time_period <- sample(rDates, size = n, TRUE) # combine this to a dataframe df <- data.frame(taxa, site, time_period) results <- WSS(df$taxa, df$site, df$time_period, minL = 4, minTP = 3, species_to_include = c('a', 'b', 'c'))#> Warning: 542 out of 1500 observations will be removed as duplicates#>#>#>#> species_name intercept.estimate year.estimate intercept.stderror #> 1 a 0.8073388 0.05120794 0.2956410 #> 2 b 0.6035651 -0.15409135 0.2836280 #> 3 c 0.4843513 0.10465525 0.2830269 #> year.stderror intercept.zvalue year.zvalue intercept.pvalue year.pvalue #> 1 0.1272529 2.730808 0.4024108 0.006317919 0.6873817 #> 2 0.1252298 2.128017 -1.2304687 0.033335712 0.2185216 #> 3 0.1221340 1.711326 0.8568889 0.087020923 0.3915063 #> observations #> 1 41 #> 2 40 #> 3 36#> $names #> [1] "species_name" "intercept.estimate" "year.estimate" #> [4] "intercept.stderror" "year.stderror" "intercept.zvalue" #> [7] "year.zvalue" "intercept.pvalue" "year.pvalue" #> [10] "observations" #> #> $class #> [1] "data.frame" #> #> $row.names #> [1] 1 2 3 #> #> $intercept_year #> [1] 2006.5 #> #> $min_year #> [1] -3.5 #> #> $max_year #> [1] 3.5 #> #> $nVisits #> [1] 60 #> #> $model_formula #> [1] "cbind(successes, failures) ~ year + (1|site)" #> #> $minL #> [1] 4 #> #> $minTP #> [1] 3 #>